Staff Backend Engineer – Platform

Responsibilities

• Design, build, and own core platform services that support Cloudinary’s backend services at scale (e.g., service mesh, shared locking, fairness and rate-limiting, and other shared infrastructure components).
• Lead end-to-end engineering initiatives - from discovery and architecture, through implementation and rollout, to observability and ongoing operations.
• Improve developer experience and productivity, evolving development environments, Blueprint projects, and frameworks that streamline service creation (e.g., Go services, AWS Lambda).
• Drive the evolution of our AI-powered operational tooling and agents, helping design, build, and maintain systems that analyze, evaluate, and assist in resolving production and on-call issues.
• Advance deployment and operational excellence, driving improvements in reliability, performance, and safety of our deployment and release lifecycle.
• Provide technical leadership and mentorship, influencing platform strategy and engineering best practices across teams and partnering closely with DevOps and product engineering.

Technical skills & experience

• 10+ years of experience in backend or platform engineering, including designing and building production systems at scale.
• Strong hands-on experience with Golang, or significant experience with another backend language with a strong desire and ability to ramp up on Go.
• Experience working with AWS and cloud-native architectures, including services such as EC2, S3, SQS, Kinesis, EKS, Lambda, Aurora, and core concepts like IAM, VPC, networking, and autoscaling.
• Proven experience designing and operating systems at scale - thinking about high availability, multi-tenancy, throughput, latency, cost, and graceful degradation rather than just correctness in small environments.
• Practical experience with Docker and containerized workloads.
• Experience with distributed systems and service-to-service communication (e.g., service meshes, RPC, concurrency, resiliency patterns).
• Experience with monitoring and observability tools, such as Kibana, Coralogix, Datadog, CloudWatch, CloudTrail, Rollbar, Athena, or similar.
• Proven technical leadership: driving complex projects, making architectural decisions, and aligning stakeholders across teams.
• Comfortable both designing and building services from scratch and working productively in large, existing codebases.

Soft skills & ways of working

• Great team player and communicator - easy to collaborate with, able to explain complex technical topics clearly to different audiences.
• Autodidact and curious, not shy about asking questions to fully understand ideas, requirements, and systems.
• Able to actively engage with other teams, understand their workflows and pain points, and translate them into practical platform solutions.
• Open-minded and collaborative, able to consider and accept other people’s ideas, even when they contradict your own.
• Growth mindset - driven to learn and improve rather than assume you already know it all.
• Comfortable mentoring and guiding other engineers, giving constructive feedback and helping raise the bar for engineering quality.
• Embraces the use of AI tools and workflows in day-to-day work, looking for ways to leverage AI to increase productivity, quality, and operational excellence rather than resisting it.

Nice to have

• Experience with at least two of Ruby, Node.js or Python and their relevant web frameworks in production systems.
• Experience with Kubernetes and container orchestration.
• Experience with ArgoCD or other GitOps deployment tools.
• Background in building internal developer platforms or shared infrastructure for other teams.
• Experience designing or integrating AI/LLM-powered operational tools or agents (for observability, incident response, or developer productivity).